Introduction. Coronary artery disease (CAD) is one of the main causes of death all over the
world. One way to reduce the mortality rate from CAD is to predict its risk and take effective …

The current development in deep learning is witnessing an exponential transition into
automation applications. This automation transition can provide a promising framework for …

The increasing availability of Electric Vehicles (EVs) is driving a shift away from traditional
gasoline-powered vehicles. Subsequently, the demand for Electric Vehicle Charging …

This study focuses on leveraging data-driven techniques to diagnose brain tumors through
magnetic resonance imaging (MRI) images. Utilizing the rule of deep learning (DL), we …

Artificial intelligence (AI) development across the health sector has recently been the most
crucial. Early medical information, identification, diagnosis, classification, then analysis …

High-speed networks are utilized to satisfy user demands by using cloud and edge services.
Due to the heterogeneous nature of these networks, security, trust, and privacy are the …

With the recent diffusion of access to publicly available large language models (LLMs),
common interest in generative artificial-intelligence-based applications for medical purposes …

The Internet of Things (IoT) has been considered in various fields in the last decade. With
the increasing number of IoT devices in the community, secure, accessible, and reliable …

Wireless sensor networks (WSNs) are a distributed collection of sensor nodes which are
distributed geographically in the deployed environment to sense the natural phenomena …

Knowledge-Defined Networking (KDN) necessarily consists of a knowledge plane for the
generation of knowledge, typically using machine learning techniques, and the …